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Chronic Pain in Hemodialysis: Beyond the Biochemical Paradigm.
No full textFor decades, the management of end-stage kidney disease (ESKD) has been clinician-led, revolving around the monthly review to assess biochemical and hematological precision. This has focused on clearance targets, electrolyte balance, and anemia correction, leaving the more subjective, patient-centered aspects of illness, such as pain and fatigue, on the periphery. For people receiving maintenance hemodialysis, it is often these symptoms that most profoundly shape daily life. In this issue of AJKD, Fischer et al1 report findings from the HOPE Consortium Trial, offering the most detailed characterization to date of chronic pain among adults receiving hemodialysis.</p
Smart Contracts and SME Resilience: Business Model Adaptation and International Considerations
No full textSmart contracts (SCs), appended to a blockchain, protect digital environments and their resources, processes and structures, reducing mismatches between legal and actual rights and ownership. They enhance digital resilience by improving transparency, traceability and trust in digital transactions. Utilizing SCs requires businesses to adapt their models, revenue streams and customer relationships. For small and medium-sized enterprises (SMEs), SCs present challenges, requiring proactive decision-making for their effective utilization and the trade-offs involved. By employing the integrated multilayer ISM-MICMAC-SWARA framework (Interpretive Structural Modelling, Cross-Impact Matrix Multiplication Applied to Classification and Stepwise Weight Assessment Ratio Analysis), we explain the complex interrelationships among the challenges and propose mitigating risk management strategies. We identify technical limitations and human errors as key drivers, confidentiality and manipulation as linkage challenges and fraud and hacking as dependence challenges. These findings highlight the interconnected nature of the challenges and their impact on SMEs, and we emphasize the need for targeted resilience strategies. Our research highlights the global dimension of SC adoption. When deploying SCs, SMEs must navigate international regulations, cross-border transactions and cultural diversity. This global perspective informs smart contracts' strategic, business and organizational aspects. Our findings offer insights for academics, industry leaders, managers and policymakers seeking to understand the potential and risks of adopting SCs in SMEs.</p
A dense web of neutral gas in a galaxy proto-cluster post-reionization
No full textGalaxy clusters are the most massive, gravitationally bound structures in the Universe. They emerged through hierarchical structure formation of large-scale dark matter and baryon overdensities. Early galaxy ‘proto-clusters’ are believed to have substantially contributed to the cosmic star-formation rate density and served as ‘hotspots’ for the reionization of the intergalactic medium. Our understanding of the formation of these structures at the earliest cosmic epochs is, however, limited to sparse observations of their galaxy members or is based on phenomenological models and cosmological simulations. Here we report the detection of a large and coherent structure of neutral atomic hydrogen gas (H i) extending from a galaxy proto-cluster at redshift z = 5.4, one billion years after the Big Bang. The presence of this H i gas is revealed by strong damped Lyman-α absorption features observed in several background-galaxy spectra. Although the sight lines overall probe a large range in H i column densities, NHI = 1020 cm−2 to 1023.5 cm−2, they are similar across nearby sight lines, demonstrating that they probe the same dense neutral gas. This observation of a dense large-scale overdensity of cold neutral gas challenges current cosmological simulations and has strong implications for the reionization topology of the Universe.</p
A Qualitative Study Examining the Application of Compression Therapy for Inpatients With Venous Leg Ulcers-Perspectives of Hospital Staff Where It Is Routinely Applied
No full textCompression therapy is the cornerstone, first-line effective evidence-based treatment for healing and managing venous leg ulcers. However, compression therapy is inconsistently applied in hospitals. This paper explores the experiences of a diverse group of clinicians and senior managers applying compression therapy in hospitals across the United Kingdom. A semi-structured qualitative interview study was conducted with 19 participants, drawn from a larger study, who confirmed that their respective hospitals apply compression therapy to inpatients with venous leg ulcers. The interviews were analysed using reflexive thematic analysis. Analysis generated four key themes: Patients 'slip through the net', Prioritisation in Hospital Care, A 'blind Spot' within Healthcare System and Motivation to Deliver Care. Patients 'slip through the net' refers to inpatients with venous leg ulcers face unequal access to compression therapy both within and between hospitals. Prioritisation in Hospital Care indicates how certain diseases are given greater emphasis within healthcare systems. A 'blind Spot' in Healthcare System described failing to implement compression therapy has created a critical underlying 'blind spot' within the NHS healthcare systems. Motivation to Deliver Care refers to a deep commitment to providing compression therapy, driven by clinicians' inherent dedication and ethical obligation towards improving patient quality of care. The study identified key challenges influencing the application of compression therapy in acute hospitals despite its routine use. These include the lottery of care, systemic inequities, unclear ownership, interprofessional disputes and organisational priorities. It also demonstrated the significant role of passion, motivation and moral responsibility encouraging clinicians to implement compression therapy despite these systemic barriers.</p
Dinâmicas do Nexus WEF na Amazônia: interações entre sistemas agrícolas, acesso a recursos e vulnerabilidades territoriais
No full textDescription</p
Bandit Neural Architecture Search for Digital Twin Optimisation: A Scientific Machine Learning Approach
No full textThe successful deployment of Digital Twins for real-time optimisation of physical systems relies critically on highly accurate and efficient deep learning surrogate models. Ensuring these models meet performance and latency requirements demands rigorous Neural Architecture Search (NAS) and Hyperparameter Optimisation (HPO). While both have been traditionally posed as a pure-exploration bandit problem, we show that it fails to capture the unique, deterministic characteristics of Scientific Machine Learning (SciML) models underpinning Digital Twins, particularly Physics-Informed Neural Networks (PINNs) and Deep Operator Networks (DeepONets). We propose a non-stochastic multi-armed bandit with balanced exploration-exploitation as the proper setting for Neural Architecture Search in Scientific Machine Learning and introduce
BanditNAS
, a novel algorithm that addresses three critical challenges absent from current approaches: (i) late convergence in high-capacity models exhibiting spectral bias, (ii) validation loss plateaus requiring optimiser switching, and (iii) the deterministic (non-stochastic) nature of physics-based training data. We analyse
BanditNAS
’s theoretical properties, proving improved regret bounds compared to adaptive adversaries, and compare it empirically with state-of-the-art approaches across three representative SciML scenarios. Our results demonstrate setting-dependent performance:
BanditNAS
achieves up to
higher optimal selection rates when multi-stage fine-tuning is required (DeepONets with L-BFGS switching), approximately
improvement in late-convergence regimes (high-capacity PINNs), and comparable performance to HyperBand in moderately noisy environments, though underperforming in very large search spaces with high noise (
graph networks). Statistical significance testing confirms
BanditNAS
’s superiority in two of three settings (
), with competitive performance in the third when restricted to
. These findings establish
BanditNAS
as a viable and theoretically grounded approach for optimising SciML models where real-time accuracy, multi-stage training, and computational resource constraints are paramount, while highlighting the importance of algorithm selection based on problem characteristics.</p
NELF prevents transcriptional readthrough into DNA replication zones in cancer cells
No full textRegulation of RNA polymerase II (Pol II) transcription is closely associated with cell proliferation. However, it remains unclear how the Pol II transcription program is rewired in cancer to promote uncontrolled growth. Here, we find that expression of NELFCD, a known negative transcription elongation factor, is upregulated in colorectal tumors. Auxin-dependent protein degradation of NELF-C in combination with nascent transcript sequencing demonstrates a direct role of NELF-C on Pol II transcription in this cancer. Strikingly, we demonstrate that the acute loss of NELF-C protein globally redistributes termination factors and perturbs Pol II transcription termination. These changes drive pervasive Pol II transcription into DNA replication zones, leading to transcription-replication conflict that may block the cell cycle in G1 or early S phase. Our findings reveal a previously unrecognized role of NELF in transcription termination and highlight NELF as a potential therapeutic target in colorectal cancer.</p
Cross-Image Feature Interaction Network for Change Detection in Remote Sensing Images
No full textRemote sensing change detection (CD) is a technique for quantitatively analyzing and determining the characteristics and processes of surface change using bi-temporal remote sensing data. Deep convolutional networks have achieved remarkable success in CD tasks. However, due to the complexity of the natural lighting environment and other factors, how to use bi-temporal images and segment objects more accurately and effectively has become a focus of research. Many existing studies have overlooked the relationship between samples, disregarding the potential connection between the same semantics across the entire sample set. Moreover, they have ignored the semantic connection between bi-temporal images and have resorted to simple techniques such as concatenation or absolute value subtraction to achieve bi-temporal feature fusion, resulting in information loss. We propose a cross-image feature interaction network consisting of three modules to address the above issues: cross-image non-local enhancement (CINE) module, which can enhance the spatial dimensional links between the same type of objects in the sample space and explores the potential relationship between the same semantics samples on the whole sample set; cross-temporal feature enhancement (CTFE) module, which interacts with bi-temporal image features to enhance real change features while suppressing irrelevant change features; and difference feature adaptive fusion (DFAF) module, which can make effective use of the bi-temporal image features extracted by the network and adaptively learns the fusion parameters. We conducted extensive experiments on two CD datasets, LEVIR-CD and DSIFN-CD, and obtained evaluation scores of 90.75%/83.07% and 69.94%/53.78% on the F1-score and IoU metrics, respectively. Our strategy surpasses existing attention-based approaches such as BIT.</p
Racial and colonial aphasia in EU border security. The case of the EU Pact on Migration and Asylum
No full textNo description supplied</p
Evolving burden and consequences of frailty in patients with acute myocardial infarction: evidence from a nationwide cohort
No full textBackground Frailty is common in acute myocardial infarction (AMI), but evidence gaps may cause care disparities and worse outcomes. We examined the prevalence of frailty, its impact on care and its long-term effects. Methods We analysed adults hospitalised with AMI in England and Wales (2005–19) using linked registries. Frailty was classified by the Secondary Care Administrative Records Frailty (SCARF) index as fit, mild, moderate or severe. The primary outcome was 1-year all-cause mortality; secondary outcomes included cardiovascular death, Major adverse cardiovascular events (MACE), heart failure readmission, reinfarction and bleeding. Results Of 931 133 patients (median age 70 years, 34% female), 13% had severe frailty, 22% moderate frailty, 36% mild frailty and 29% were classified as fit. Compared with fit patients, those with severe frailty were less likely to receive coronary angiography (44.8% vs. 69.3%), dual antiplatelet therapy (75.5% vs. 93.4%) or referral for cardiac rehabilitation (71.8% vs. 89.7%). Frailty demonstrated a graded association with 1-year mortality: aHR:3.01 (95% CI:2.93–3.10) for severe frailty, 2.33 (95% CI:2.27–2.40) for moderate and aHR:1.65 (95% CI:1.61–1.7) for mild frailty. Similar dose–response patterns were seen for cardiovascular death (aHR:2.82, 95% CI:2.70–2.94; 2.03, 95% CI:1.88–2.20; and 1.12, 95% CI:1.08–1.16), MACE (aHR:2.56, 95% CI:2.51–2.60; 1.84, 95% CI:1.80–1.89; and 1.17, 95% CI:1.15–1.19), heart failure readmission (aHR:3.74, 95% CI:3.61–3.88; 2.79, 95% CI:2.69–2.89; and 1.79, 95% CI:1.73–1.85) and major bleeding (aHR:1.85, 95% CI:1.78–1.92; 1.59, 95% CI:1.51–1.67; and 1.27, 95% CI:1.20–1.34). Conclusion In this national cohort, over one-third of AMI patients had moderate or severe frailty, which was associated with reduced use of evidence-based care and worse outcomes.</p